摘要
针对双有源桥(DAB)变换器传统模型预测控制(MPC)输出电压性能对系统参数变化较为敏感的问题,提出一种基于自适应参数辨识的DAB变换器鲁棒预测控制方法。本研究采用递归最小二乘法构建参数辨识矩阵,通过在线实时校正DAB系统的电感与电容动态参数,有效增强了MPC在变工况下的鲁棒特性;通过参数误差反馈及门槛值设置,在每个控制周期中根据误差大小自适应调整遗忘因子,提高参数辨识准确性及收敛速度;结合系统采样和参数辨识结果,实现未来时刻的电压预测,并通过价值函数评估最优移相角,应用在下一个控制周期。该方法可以实时辨识DAB系统电感和电容参数,消除了参数失配对预测控制的影响,保证了输出电压性能。最后,通过仿真和硬件实验平台验证了所提方法在稳态、动态以及参数辨识下的运行性能。
To solve the problem that the output voltage performance of conventional model predictive control(MPC)under dual active bridge(DAB)converter is sensitive to the change of system parameters,a robust predictive control method based on adaptive parameter identification was proposed for DAB converter.In this study,a recursive least squares algorithm was used to construct the parameter identification matrix,and the dynamic parameters of the inductance and capacitor of the DAB system were corrected online in real time,which effectively enhances the robust characteristics of MPC under variable operating conditions.Through parameter error feedback and threshold setting,the forgetting factor was adjusted adaptively according to the error size in each control period to improve the accuracy of parameter identification and convergence speed.Combined with the results of system sampling and parameter identification,the voltage prediction at future time is realized,and the optimal phase shift angle is evaluated by cost function and applied to the next control period.This method can identify the inductance and capacitance parameters of DAB system in real time,eliminate the influence of parameter mismatch predictive control,and ensure the output voltage performance.Finally,the performance of the proposed method under steady state,dynamic state and parameter identification was verified by simulation and hardware experiment platform.
作者
尹政
邓富金
黄堃
詹昕
YIN Zheng;DENG Fujin;HUANG Kun;ZHAN Xin(School of Electrical Engineering,Southeast University,Nanjing 210096,China;State Grid NARI Technology Company Ltd.,Nanjing 211106,China;School of Electronic Science&Engineering,Southeast University,Nanjing 210096,China;Yangzhou Power Supply Company of State Grid Jiangsu Electric Power Co.,Ltd.,Yangzhou 225000,China)
出处
《电机与控制学报》
北大核心
2025年第2期74-84,95,共12页
Electric Machines and Control
基金
国家重点研发计划“政府间国际科技创新合作”重点专项(2022YFE0196300)。
关键词
双有源桥变换器
模型预测控制
参数辨识
递归最小二乘法
自适应遗忘因子
鲁棒性
dual active bridge converter
model predictive control
parameter identification
recursive least-square method
adaptive forgetting factor
robustness
